The kube-apiserver validation expects the Count of an EventSeries to be
at least 2, otherwise it rejects the Event. There was is discrepancy
between the client and the server since the client was iniatizing an
EventSeries to a count of 1.
According to the original KEP, the first event emitted should have an
EventSeries set to nil and the second isomorphic event should have an
EventSeries with a count of 2. Thus, we should matcht the behavior
define by the KEP and update the client.
Also, as an effort to make the old clients compatible with the servers,
we should allow Events with an EventSeries count of 1 to prevent any
unexpected rejections.
Signed-off-by: Damien Grisonnet <dgrisonn@redhat.com>
Implement DOS prevention wiring a global rate limit for podresources
API. The goal here is not to introduce a general ratelimiting solution
for the kubelet (we need more research and discussion to get there),
but rather to prevent misuse of the API.
Known limitations:
- the rate limits value (QPS, BurstTokens) are hardcoded to
"high enough" values.
Enabling user-configuration would require more discussion
and sweeping changes to the other kubelet endpoints, so it
is postponed for now.
- the rate limiting is global. Malicious clients can starve other
clients consuming the QPS quota.
Add e2e test to exercise the flow, because the wiring itself
is mostly boilerplate and API adaptation.
We have quite a few podresources e2e tests and, as the feature
progresses to GA, we should consider moving them to NodeConformance.
Unfortunately most of them require linux-specific features not in the
test themselves but in the test prelude (fixture) to check or create the
node conditions (e.g. presence or not of devices, online CPUS...) to be
verified in the test proper.
For this reason we promote only a single test for starters.
Signed-off-by: Francesco Romani <fromani@redhat.com>
Since we can't rely on the test runner and hosts under test to
be on the same machine, we write to the terminate log from each
container and concatenate the results.
If a CRI error occurs during the terminating phase after a pod is
force deleted (API or static) then the housekeeping loop will not
deliver updates to the pod worker which prevents the pod's state
machine from progressing. The pod will remain in the terminating
phase but no further attempts to terminate or cleanup will occur
until the kubelet is restarted.
The pod worker now maintains a store of the pods state that it is
attempting to reconcile and uses that to resync unknown pods when
SyncKnownPods() is invoked, so that failures in sync methods for
unknown pods no longer hang forever.
The pod worker's store tracks desired updates and the last update
applied on podSyncStatuses. Each goroutine now synchronizes to
acquire the next work item, context, and whether the pod can start.
This synchronization moves the pending update to the stored last
update, which will ensure third parties accessing pod worker state
don't see updates before the pod worker begins synchronizing them.
As a consequence, the update channel becomes a simple notifier
(struct{}) so that SyncKnownPods can coordinate with the pod worker
to create a synthetic pending update for unknown pods (i.e. no one
besides the pod worker has data about those pods). Otherwise the
pending update info would be hidden inside the channel.
In order to properly track pending updates, we have to be very
careful not to mix RunningPods (which are calculated from the
container runtime and are missing all spec info) and config-
sourced pods. Update the pod worker to avoid using ToAPIPod()
and instead require the pod worker to directly use
update.Options.Pod or update.Options.RunningPod for the
correct methods. Add a new SyncTerminatingRuntimePod to prevent
accidental invocations of runtime only pod data.
Finally, fix SyncKnownPods to replay the last valid update for
undesired pods which drives the pod state machine towards
termination, and alter HandlePodCleanups to:
- terminate runtime pods that aren't known to the pod worker
- launch admitted pods that aren't known to the pod worker
Any started pods receive a replay until they reach the finished
state, and then are removed from the pod worker. When a desired
pod is detected as not being in the worker, the usual cause is
that the pod was deleted and recreated with the same UID (almost
always a static pod since API UID reuse is statistically
unlikely). This simplifies the previous restartable pod support.
We are careful to filter for active pods (those not already
terminal or those which have been previously rejected by
admission). We also force a refresh of the runtime cache to
ensure we don't see an older version of the state.
Future changes will allow other components that need to view the
pod worker's actual state (not the desired state the podManager
represents) to retrieve that info from the pod worker.
Several bugs in pod lifecycle have been undetectable at runtime
because the kubelet does not clearly describe the number of pods
in use. To better report, add the following metrics:
kubelet_desired_pods: Pods the pod manager sees
kubelet_active_pods: "Admitted" pods that gate new pods
kubelet_mirror_pods: Mirror pods the kubelet is tracking
kubelet_working_pods: Breakdown of pods from the last sync in
each phase, orphaned state, and static or not
kubelet_restarted_pods_total: A counter for pods that saw a
CREATE before the previous pod with the same UID was finished
kubelet_orphaned_runtime_pods_total: A counter for pods detected
at runtime that were not known to the kubelet. Will be
populated at Kubelet startup and should never be incremented
after.
Add a metric check to our e2e tests that verifies the values are
captured correctly during a serial test, and then verify them in
detail in unit tests.
Adds 23 series to the kubelet /metrics endpoint.
